Delineating the Reaction Mechanism and Cation Effects for Electrocatalytic CO2 Reduction to C2+ products using Graph Theory and Microkinetic Modelling Analyses
Ranga Rohit Seemakurthi a, Santiago Morandi a, Núria López a
a Institute of Chemical Research of Catalonia (ICIQ), Barcelona Institute of Science and Technology (BIST), ES
Proceedings of International Conference on Frontiers in Electrocatalytic Transformations (INTERECT22)
València, Spain, 2022 November 21st - 22nd
Organizers: Sara Barja, Nongnuch Artrith and Matthew Mayer
Oral, Ranga Rohit Seemakurthi, presentation 023
Publication date: 11th October 2022

Conversion of CO2 to multi-carbon products using renewable electricity is a viable strategy to reduce the greenhouse gas effects and produce high-value chemicals in a sustainable manner. However, the commercial viability of this process is severely affected due to the low selectivities, or faradaic efficiencies (FEs) of the hydrocarbons and alcohols produced. Even though there has been a lot of research towards finding better catalysts for converting CO2 to C2+ products selectively, copper remains the state-of-the-art catalyst for this conversion[1]. Recent work has shown that larger hydrocarbons beyond C2 can be formed on oxide-derived Cu and Ni catalysts with non-trivial faradaic efficiencies (~25%) [2,3]. This remains a widely underexplored area and holds great prominence due to the high value of C3+ products, which can further improve the economics of e-CO2RR. Even though promising, the reaction mechanisms for C3+ product formation involve large reaction networks with several surface intermediates (>100). In addition, electrolyte effects including pH and cation are found to influence the CO2 activation and C-C bond formation reaction steps [1]. Therefore, in this study, we develop a detailed microkinetic model to first understand the reaction mechanism towards the various C2 and C3 products on Cu catalysts. We also test the influence of cations on the rate determining steps to evaluate their effect on different product selectivities. 

Firstly, we identified all the possible reaction paths for the C2+ products using an in-house graph-theory based algorithm ‘r-net’. We then found all the unique sites on the Cu (100) and automatically placed the reaction intermediates on the identified sites using the ‘catkit’ algorithm. Once the transition state energies were evaluated, all the energetics data has been stored in a python-based ASE database. This database serves as an input for our microkinetic modelling code ‘pyMKM’. The initial results from the model showed that most abundant surface intermediate is CO* for which the coverages are high. Hence, we performed a coverage dependent analysis on the most important reaction intermediates and reaction steps that are found through the degree of rate control analysis. Additionally, we evaluated the effect of cations on these pathways through which the lower on-set potential of C2 products as compared to C1 products was correctly predicted. The selectivity determining C-C bond steps that lead to propanol formation have also been ascertained. The ultimate aim of the study would be to further evaluate the identified pathways on oxide-derived Cu models to understand the influence of Cu oxidation state towards selectivity of hydrocarbon products. 

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